A measure of how often a given vertex lies on the shortest path between two other vertices, or the vertex’s role as a ‘bridge’/ quantifies the number of times a node acts as a bridge along the shortest path between two other nodes.

Broker

Bridge that acts as a link between nodes

Centrality

How important a vertex is within the network

Closeness centrality

The average distance between a vertex and every other vertex in the network, measures to what extent the vertex is directly connected to others in network. Measuring closeness in a twitter network allows a researcher to measure of how long it will take to spread information from the main node to all other nodes sequentially.

Clustering coefficient

Measurement of density in a 1.5 degree network

Component

A disconnected piece of a single network

Degree centrality

Overall number if edges connected to a particular vertex (i.e. the number of ties that a node has)

Ego

The person who is the focus of the study

Eigenvector centrality

Measures the extent to which a vector’s connections are well connected (i.e measures the influence of a node in a network.

Group

Vertices that are well connected to each other than they are to others in the network. Groups emerge as highly interconnected sets of actors known as cliques and clusters

In-degree

A count of the number of ties directed to the node/The number of connections that point inward at a vertex. When ties are associated to some positive aspects such as friendship or collaboration. It is often interpreted as a form of popularity

Network Density

Measures the extent to which vertices are highly connected. Measures the number of “actual” relations or ties as a proportion of the number of theoretically possible relations or ties

Node

A connection point

Out-degree

The number of ties that the node directs to others.

Range

Varying size and heterogeneity of social networks

Structural hole

A third person who bridges the gap between pairs which are not directly connected.